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CN113762814A - Method and device for warehousing articles - Google Patents

Method and device for warehousing articles Download PDF

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Publication number
CN113762814A
CN113762814A CN202010489240.8A CN202010489240A CN113762814A CN 113762814 A CN113762814 A CN 113762814A CN 202010489240 A CN202010489240 A CN 202010489240A CN 113762814 A CN113762814 A CN 113762814A
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storage
warehousing
article
articles
historical
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CN113762814B (en
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姜盛乾
刘伟
张月
康胜苏
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Beijing Jingdong Zhenshi Information Technology Co Ltd
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Beijing Jingdong Zhenshi Information Technology Co Ltd
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Abstract

The invention discloses a method and a device for warehousing articles, and relates to the technical field of warehousing. One embodiment of the method comprises: acquiring historical warehousing article information and warehousing information, and classifying storage areas according to the historical warehousing article information and the warehousing information; constructing a storage space planning model according to the storage space classification result, the picking cost and the restriction condition of each storage space in the storage space, and determining a storage space set corresponding to each type of warehousing goods according to the storage space planning model; and according to the types of the articles to be warehoused, determining a target storage position in the corresponding storage position set for warehousing and storing the articles. The embodiment provides an effective and reasonable article warehousing method, and article storage difficulty and storage cost are reduced.

Description

Method and device for warehousing articles
Technical Field
The invention relates to the technical field of warehousing, in particular to a method and a device for warehousing articles.
Background
With the rise of intelligent manufacturing, the development of the discrete manufacturing industry is rapid in recent years, particularly the textile industry is rapidly changed, and meanwhile, the storage of related articles in a warehouse is greatly challenged. Taking the clothing industry as an example, the method relates to warehousing operation of warehousing and ex-warehousing of raw materials (such as clothing lining and the like) and warehousing of finished clothes after the production of the clothes.
In the process of implementing the invention, the inventor finds that at least the following problems exist in the prior art:
1. the existing article warehousing storage method lacks effective and reasonable storage planning, so that the article storage difficulty is high and the storage cost is high;
2. after discrete articles generated when the complete articles are not used up are put in storage, the discrete articles need to be preferentially taken out of the storage when used next time, and a storage method aiming at the discrete articles is not involved in the existing method.
Disclosure of Invention
In view of this, embodiments of the present invention provide an article warehousing method and apparatus, which can provide an effective and reasonable article warehousing storage method, and reduce article storage difficulty and article storage cost.
In order to achieve the above object, according to a first aspect of an embodiment of the present invention, there is provided an article warehousing method including:
acquiring historical warehousing article information and warehousing information, and classifying storage areas according to the historical warehousing article information and the warehousing information;
constructing a storage space planning model according to the storage space classification result, the picking cost and the restriction condition of each storage space in the storage space, and determining a storage space set corresponding to each type of warehousing goods according to the storage space planning model;
and according to the types of the articles to be warehoused, determining a target storage position in the corresponding storage position set for warehousing and storing the articles.
Further, the historical warehousing item information includes: the types of the historical warehousing articles, and the storage spaces and the turnover rates corresponding to the various types of the historical warehousing articles; the warehousing information includes: the storage areas, storage locations and the picking distance between the storage locations and the storage entrances in the storage.
Further, the step of classifying the storage areas according to the historical warehousing article information and the warehousing information comprises the following steps: and determining volume order indexes of various types of historical warehousing articles according to the historical warehousing article information, and classifying storage areas according to the volume order indexes and the warehousing information.
Further, the step of determining the average storage amount of each type of historical warehousing articles according to the historical warehousing article information, and the step of classifying the storage areas according to the volume order index and the warehousing information comprises the following steps: sorting the volume order indexes of various types of historical warehousing articles according to the numerical value, storing and classifying the historical warehousing articles according to the sorting result, and classifying the storage areas according to the storage classification result, the average storage amount, the warehousing information and the storage area classification rule.
Further, the storage area classification result indicates the picking distance between each storage position in the storage area and the storage entrance and the picking frequency of each type of historical warehousing articles, and the step of constructing the storage position planning model according to the storage area classification result, the picking cost of each storage position in the storage area and the constraint condition comprises the following steps: and constructing a storage space planning model according to the picking distance and picking cost corresponding to each storage space, the picking frequency corresponding to each type of historical warehousing article and the constraint conditions.
Further, the constraint conditions comprise warehousing article type constraint and storage location constraint.
Further, the types of the articles to be warehoused comprise article types and article forms, wherein the article forms comprise whole and scattered articles; before the step of determining the target storage location in the corresponding storage location set for article warehousing storage according to the type of the article to be warehoused, the article warehousing method further comprises the following steps: determining the level numerical values corresponding to different levels of each shelf in the warehouse according to a normal distribution function, and determining the target storage positions of scattered articles corresponding to each type of warehoused articles according to the level numerical values, the picking distance between each storage position and the warehouse entrance and the storage position set corresponding to each type of warehoused articles.
Further, the storage set comprises scattered article target storage positions and integral article target storage positions, and the step of determining the target storage positions in the corresponding storage position sets for article warehousing storage according to the types of articles to be warehoused comprises the following steps: determining a corresponding storage position set according to the category of the articles to be warehoused, and storing the articles to be warehoused to the corresponding target storage positions of the whole articles under the condition that the articles to be warehoused are the whole articles; and under the condition that the articles to be warehoused are scattered articles, storing the articles to be warehoused to the corresponding scattered article target storage positions.
Further, under the condition that the target storage location corresponding to the article to be warehoused is not an empty storage location, the article warehousing method further comprises the following steps: and determining corresponding empty storage positions according to the picking distance between each storage position and the storage entrance to store the articles in a warehouse.
Further, the article is an article for production in a discrete manufacturing industry.
According to a second aspect of the embodiments of the present invention, there is provided an article warehousing device including:
the storage area classification module is used for acquiring information of historical warehousing articles and warehousing information and classifying the storage areas according to the information of the historical warehousing articles and the warehousing information;
the storage position set determining module is used for constructing a storage position planning model according to the storage area classification result, the picking cost and the restriction condition of each storage position in the storage area, and determining a storage position set corresponding to each type of warehousing goods according to the storage position planning model;
and the article warehousing module is used for determining a target storage position in the corresponding storage position set according to the type of the article to be warehoused for article warehousing storage.
According to a third aspect of embodiments of the present invention, there is provided an electronic apparatus, including:
one or more processors;
a storage device for storing one or more programs,
when executed by one or more processors, cause the one or more processors to implement any of the methods of warehousing items as described above.
According to a fourth aspect of embodiments of the present invention, there is provided a computer-readable medium, on which a computer program is stored, which when executed by a processor, implements any of the above-described methods of warehousing an item.
One embodiment of the above invention has the following advantages or benefits: because the information of the historical warehousing articles and the warehousing information are obtained, the storage areas are classified according to the information of the historical warehousing articles and the warehousing information; constructing a storage space planning model according to the storage space classification result, the picking cost and the restriction condition of each storage space in the storage space, and determining a storage space set corresponding to each type of warehousing goods according to the storage space planning model; according to the type of the articles to be put in storage, the technical means of intensively determining the target storage positions in the corresponding storage positions for article putting in storage is adopted, so that the technical problems of high article storage difficulty and high storage cost caused by lack of effective and reasonable article storage planning in the existing article storage method are solved, an effective and reasonable article putting in storage method is further provided, and the technical effects of reducing the article storage difficulty and the article storage cost are achieved.
Further effects of the above-mentioned non-conventional alternatives will be described below in connection with the embodiments.
Drawings
The drawings are included to provide a better understanding of the invention and are not to be construed as unduly limiting the invention. Wherein:
fig. 1 is a schematic view of a main flow of an article warehousing method provided according to a first embodiment of the present invention;
fig. 2 is a schematic view of a main flow of an article warehousing method according to a second embodiment of the present invention;
fig. 3 is a schematic diagram of main modules of an article warehousing device provided according to an embodiment of the invention;
FIG. 4 is an exemplary system architecture diagram in which embodiments of the present invention may be employed;
fig. 5 is a schematic block diagram of a computer system suitable for use in implementing a terminal device or server of an embodiment of the invention.
Detailed Description
Exemplary embodiments of the present invention are described below with reference to the accompanying drawings, in which various details of embodiments of the invention are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the invention. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
Fig. 1 is a schematic view of a main flow of an article warehousing method provided according to a first embodiment of the present invention; as shown in fig. 1, the method for warehousing articles provided by the embodiment of the present invention mainly includes:
and S101, acquiring historical warehousing article information and warehousing information, and classifying storage areas according to the historical warehousing article information and the warehousing information.
Through the arrangement, the storage area classification is carried out according to the historical warehousing article information and the warehousing information, so that the storage position sets corresponding to various types of warehousing articles can be determined according to the storage area classification results, the storage units corresponding to the warehousing articles can be distributed more reasonably, and the difficulty and the storage cost of warehousing and storing the articles can be reduced.
Specifically, according to an embodiment of the present invention, the historical warehousing item information includes: the types of the historical warehousing articles, and the storage spaces and the turnover rates corresponding to the various types of the historical warehousing articles; the warehousing information comprises: the storage areas, storage locations and the picking distance between the storage locations and the storage entrances in the storage.
Historical warehousing article information can be acquired according to storage data in a past warehousing period (a specific time period can be adjusted according to actual conditions); the storage information is directly determined according to the storage areas, the storage shelves and the storage position distribution on the storage shelves in the storage.
According to the embodiment of the invention, the step of classifying the storage areas according to the historical warehousing article information and the warehousing information comprises the following steps: and determining volume order indexes of various types of historical warehousing articles according to the historical warehousing article information, and classifying storage areas according to the volume order indexes and the warehousing information.
Volume Order Index (COI, Cube-Per-Order Index): refers to the total storage space C required for storing some type of article p in a certain period of timepAnd the turnover rate f of the article in the period of timepIn particular COIp＝Cp/fp(ii) a The classified storage based on COI not only considers the turnover rate of the stored articles, but also considers the storage space of the stored articles, and further improves the efficiency and rationality of the warehousing and storage of the articles.
According to a specific implementation manner of the embodiment of the present invention, EIQ (created by suzuki earthquake, which is a japanese logistics expert, is determined for each type of article) corresponding to each type of article according to the historical warehousing article information, and three key elements, namely, an order Entry (corresponding to each warehousing Entry, for recording the type, Quantity, and the like of the warehoused articles), an article type Item, and an article Quantity (corresponding to the Quantity of the warehoused articles) are mainly considered, and then storage area classification is performed according to the COI index and EIQ analysis method.
Further, according to the embodiment of the present invention, the method for warehousing articles further includes: determining the average storage capacity of various types of historical warehousing articles according to the historical warehousing article information; the step of classifying the storage area according to the volume order index and the warehousing information comprises the following steps: sorting the volume order indexes of various types of historical warehousing articles according to the numerical value, storing and classifying the historical warehousing articles according to the sorting result, and classifying the storage areas according to the storage classification result, the average storage amount, the warehousing information and the storage area classification rule.
According to a specific implementation manner of the embodiment of the present invention, the storage area classification rule is an ABC classification rule, which is also called an ABC classification management inventory control method and a primary and secondary factor analysis method and is originally created by the italian economist vilfreudeno pareto. The ABC analysis method is an analysis method commonly used in storage management, and is an analysis method for performing classification queuing, distinguishing emphasis from generality and determining management modes differently according to the main characteristics of things in technical or economic aspects. It is also called ABC analysis because it divides the objects being analyzed into A, B, C three classes. The specific proportion settings for the A, B, C categories can be adjusted according to actual conditions.
According to a specific implementation manner of the embodiment of the present invention, the COI values corresponding to all types of historical warehousing articles are arranged in the order from small to large, and then the historical warehousing articles are sorted according to the ratio of 2:3:5 (the category refers to a large category, which includes a plurality of specific warehousing article categories), that is, the top 20% of the historical warehousing articles are classified as a category, the middle 50% of the articles are classified as a category B, and the last 50% of the historical warehousing articles are classified as a category C. The specific storage classification ratio may be set according to actual conditions, the numerical values corresponding to the above ratios are only examples, and similarly, the grades of the specific classification categories may also be set according to actual conditions, and are not limited to the A, B, C categories described in the above embodiments of the present invention.
According to another specific implementation manner of the embodiment of the present invention, the average storage amount of each type of warehousing articles is obtained by calculating the total warehousing storage data of each type of warehousing articles in multiple inventories in the extractable historical article warehousing information, then storage classification results of the historical warehousing data are combined to obtain A, B, C types of corresponding storage data (i.e. storage units required by each type in A, B, C), storage area classification is performed by combining the warehousing information and the storage area classification rules, and the storage area required by each type (i.e. the aforementioned A, B, C types) of historical warehousing articles is determined.
And S102, constructing a storage space planning model according to the storage space classification result, the picking cost and the restriction condition of each storage space in the storage space, and determining a storage space set corresponding to each type of warehousing goods according to the storage space planning model.
Through the arrangement, the storage units corresponding to the warehoused articles are refined to the storage level, so that the storage units corresponding to various types of warehoused articles are more accurate, and the warehousing difficulty of the articles is obviously reduced.
Specifically, according to the embodiment of the present invention, the storage area classification result indicates the picking distance between each storage position in the storage area and the storage entrance and the picking frequency of each type of historical warehousing item.
Wherein, the picking frequency is determined according to the picking amount in a certain time; the picking distance comprises a horizontal distance and a vertical distance, the horizontal picking distance from the storage entrance to the same shelf is equal, and the vertical picking distances from the storage positions of different levels to the storage entrance to the same shelf are respectively unequal.
Further, according to an embodiment of the present invention, the step of constructing the storage space planning model according to the storage area classification result, the picking cost of each storage space in the storage area, and the constraint condition includes: and constructing a storage space planning model according to the picking distance and picking cost corresponding to each storage space, the picking frequency corresponding to each type of historical warehousing article and the constraint conditions.
It should be noted that, in the process of constructing the storage space planning model, the picking frequency corresponding to each type of historical warehousing item needs to be converted into the picking amount in the corresponding picking period to participate in the construction of the storage space planning model.
Further, according to a specific implementation manner of the embodiment of the present invention, for an article warehousing method including scattered articles, the step of constructing the storage space planning model according to the storage area classification result, the picking cost of each storage space in the storage area, and the constraint condition includes: and constructing a storage space planning model according to the picking distance and picking cost corresponding to each storage space, the picking frequency corresponding to each type of historical warehousing article, the warehousing coefficient of scattered articles of each storage space and the constraint conditions. The warehousing frequency of the scattered articles in the storage positions in the picking period is indicated by the warehousing coefficient of the scattered articles of each storage position, and the higher the warehousing frequency of the scattered articles is, the larger the corresponding warehousing coefficient of the scattered articles is.
According to the embodiment of the invention, the constraint conditions comprise warehouse entry article type constraint and storage position constraint.
And (4) restricting the types of the articles to be put in storage: each storage unit (storage position) can only store one type of article;
and (4) storage position constraint: the reserve is an 0/1 variable that can only be allocated to a certain type of item or not.
And S103, determining a target storage position in the corresponding storage position set according to the type of the article to be stored in the storage position set for article storage.
Specifically, according to the embodiment of the present invention, the types of the articles to be warehoused include article types and article forms, wherein the article forms include whole and scattered articles.
The item type is determined by the attribute of the item; the article form in the present invention refers to the article as a whole or as a discrete article (a part of the article is consumed), and does not refer to a certain shape state of the article.
According to the embodiment of the invention, before the step of determining the target storage location in the corresponding storage location set for storing the articles in the storage according to the type of the articles to be stored in the storage, the method for storing the articles in the storage further comprises the following steps: determining the level numerical values corresponding to different levels of each shelf in the warehouse according to a normal distribution function, and determining the target storage positions of scattered articles corresponding to each type of warehoused articles according to the level numerical values, the picking distance between each storage position and the warehouse entrance and the storage position set corresponding to each type of warehoused articles.
For the articles to be stored which have an integral state and a scattered state, the determined storage position set is divided into the scattered article target storage position and the integral article target storage position through the setting, the articles can be stored in a warehouse more effectively, the storage positions which are concentrated and are closer to the storage inlet can be set as the scattered article target storage positions, and the scattered articles can be discharged from the warehouse preferentially.
Specifically, according to an embodiment of the present invention, the storage set includes a scattered item target bin and a whole item target bin. The residual storage positions of the storage positions with the scattered object target storage positions removed in the concentrated mode are the integral object target storage positions.
Further, according to the embodiment of the present invention, the step of determining the target storage location in the corresponding storage location set according to the type of the article to be warehoused for warehousing and storing the article includes: determining a corresponding storage position set according to the category of the articles to be warehoused, and storing the articles to be warehoused to the corresponding target storage positions of the whole articles under the condition that the articles to be warehoused are the whole articles; and under the condition that the articles to be warehoused are scattered articles, storing the articles to be warehoused to the corresponding scattered article target storage positions.
And when the articles to be warehoused are warehoused and stored, randomly warehousing the articles in the corresponding target storage positions.
According to the embodiment of the invention, under the condition that the target storage position corresponding to the article to be warehoused is not an empty storage position, the article warehousing method further comprises the following steps: and determining corresponding empty storage positions according to the picking distance between each storage position and the storage entrance to store the articles in a warehouse.
Specifically, according to a specific implementation manner of the embodiment of the present invention, according to the arrangement of the storage areas, the shelves, and the storage locations, an empty storage location closest to the target storage location corresponding to the type of the article to be warehoused is calculated for warehousing the article.
In particular, according to an embodiment of the present invention, the above-mentioned article is an article for production in the discrete manufacturing industry. Such as lining materials in the clothing industry, raw materials in the chemical industry and the like.
According to the technical scheme of the embodiment of the invention, the storage area classification is carried out according to the information of the historical warehousing articles and the warehousing information by acquiring the information of the historical warehousing articles and the warehousing information; constructing a storage space planning model according to the storage space classification result, the picking cost and the restriction condition of each storage space in the storage space, and determining a storage space set corresponding to each type of warehousing goods according to the storage space planning model; according to the type of the articles to be put in storage, the technical means of intensively determining the target storage positions in the corresponding storage positions for article putting in storage is adopted, so that the technical problems of high article storage difficulty and high storage cost caused by lack of effective and reasonable article storage planning in the existing article storage method are solved, an effective and reasonable article putting in storage method is further provided, and the technical effects of reducing the article storage difficulty and the article storage cost are achieved.
Fig. 2 is a schematic view of a main flow of an article warehousing method according to a second embodiment of the present invention; as shown in fig. 2, an application scenario of the embodiment of the present invention is storage of a lining fabric in a clothing industry, and the method for warehousing an article provided by the embodiment of the present invention mainly includes:
step S201, historical warehousing article information and warehousing information are obtained, and volume order indexes and average storage quantity of various types of historical warehousing articles are determined according to the historical warehousing article information.
Specifically, according to an embodiment of the present invention, the historical warehousing item information includes: the types of the historical warehousing articles, and the storage spaces and the turnover rates corresponding to the various types of the historical warehousing articles; the warehousing information comprises: the storage areas, storage locations and the picking distance between the storage locations and the storage entrances in the storage.
The historical warehousing article information can be obtained according to surface and lining material storage data which are stored in a warehouse in a middle and small clothing factory building in the past period of time (the specific time period can be adjusted according to actual conditions) in the corresponding warehouse; the storage information is directly determined according to the storage areas, the storage shelves and the storage position distribution on the storage shelves in the storage. Through the arrangement, the storage area classification is carried out according to the historical warehousing article information and the warehousing information, so that the storage position sets corresponding to various types of warehousing articles can be determined according to the storage area classification results, the storage units corresponding to the warehousing articles can be distributed more reasonably, and the difficulty and the storage cost of warehousing and storing the articles can be reduced.
According to a specific implementation manner of the embodiment of the invention, total warehousing storage books of various types of profile linings in the past 10 times of inventory can be randomly extracted, and then the average storage capacity (marked as beta) of the various types of warehousing surface linings can be respectively calculated1、β2、…βnAnd n represents the total type number of the facing material).
Step S202, the volume order indexes of various types of historical warehousing articles are sorted according to the numerical value, the historical warehousing articles are stored and classified according to the sorting result, and the storage areas are classified according to the storage and classification result, the average storage amount, the warehousing information and the storage area classification rule.
According to a specific implementation manner of the embodiment of the present invention, the COI values corresponding to all types of historical warehousing articles are arranged in the order from small to large, and then the historical warehousing articles are sorted according to the ratio of 2:3:5 (the category refers to a large category, which includes a plurality of specific warehousing article categories), that is, the top 20% of the historical warehousing articles are classified as a category, the middle 50% of the articles are classified as a category B, and the last 50% of the historical warehousing articles are classified as a category C. The specific storage classification ratio may be set according to actual conditions, the numerical values corresponding to the above ratios are only examples, and similarly, the grades of the specific classification categories may also be set according to actual conditions, and are not limited to the A, B, C categories described in the above embodiments of the present invention. Then, the storage classification results of the historical warehousing data are combined, and A, B, C three types of corresponding storage data (namely, A, B, C storage units alpha required by each large type of storage data are obtained through calculationA、αB、αC) Combining the storage information (dividing the storage into multiple storage areas, marking the shelf of each storage area from the shelf of each storage area to the storageThe picking distance of the inlet is required to be known and is arranged from near to far according to the picking distance) and a storage classification rule are adopted to classify the storage, that is, not less than alpha is extracted from the total storage units (storage area, accurate to goods shelf) in the warehouseAThe goods shelf is used for storing the A-type flour and lining materials, and the extraction is not less than alphaBThe shelf is used for storing the B-type surface lining materials, and the rest shelves are used for storing the C-type surface lining materials.
Step S203, a storage space planning model is constructed according to the storage space classification result, the picking cost and the constraint condition of each storage space in the storage space.
According to the setting of the embodiment of the invention, the storage space planning model aims to minimize the inventory cost of the articles, and the purchase quantity (equal to the warehousing quantity) of the materials on the warehousing surface is made according to the production plan of the factory building, so the embodiment of the invention only considers the sorting cost, including the warehousing sorting cost and the ex-warehousing sorting cost, and for the same article, the warehousing sorting cost is equal to the ex-warehousing sorting cost.
Specifically, according to the embodiment of the present invention, the storage area classification result indicates the picking distance between each storage position in the storage area and the storage entrance and the picking frequency of each type of historical warehousing item.
According to the embodiment of the invention, a storage planning model is constructed as follows:
Figure BDA0002520412530000121
wherein h represents an article grid (one storage position corresponds to one article grid, and only the storage position allocated with the article grid can be used for storing articles in a warehouse), k represents a storage position, and l representskRepresenting the picking distance between the storage location and the storage entrance; dhIndicating the picking quantity of the object grid h in a picking period T (the picking frequency is determined according to the picking quantity in a picking period); fhRepresents the picking cost of the item bin h; ghThe excess stock warehousing coefficient (i.e. the scattered article warehousing coefficient which indicates the warehousing frequency of the excess stock in the article grid in the sorting period, the more the warehousing frequency of the excess stock isHigh, the greater the corresponding residue storage factor).
According to the embodiment of the invention, the constraint conditions comprise warehouse entry article type constraint and storage position constraint.
And (4) restricting the types of the articles to be put in storage: each storage unit (storage position) can only store one type of article; specifically, it can be expressed as:
Figure BDA0002520412530000122
and (4) storage position constraint: the storage position is 0/1 variable, which can be only allocated to a certain type of article or not allocated, and can be specifically expressed as:
Figure BDA0002520412530000123
Figure BDA0002520412530000124
and step S204, determining a storage space set corresponding to each type of warehousing goods according to the storage space planning model.
According to the embodiment of the invention, the storage space planning model can be solved according to a heuristic algorithm or an exhaustive method, and the storage space corresponding to each object lattice (each object lattice corresponds to one type of surface material and lining material) is obtained. And (4) adding the excess material warehousing coefficient because the excess material of the flour lining material needs to be taken out of the warehouse preferentially after being warehoused, and placing the flour lining material with higher excess material warehousing frequency in a storage position considering a warehousing entrance.
And S205, determining the level numerical values corresponding to different levels of each shelf in the warehouse according to the normal distribution function, and determining the target storage positions of scattered articles corresponding to each type of warehoused article according to the level numerical values, the sorting distance between each storage position and the warehouse entrance and the storage position set corresponding to each type of warehoused article.
Specifically, according to the embodiment of the present invention, the number of floors per shelf is assigned from bottom to top, and assuming that the number of floors is k phi, the score of each floor is respectively
Figure BDA0002520412530000131
(
Figure BDA0002520412530000132
Normal distribution functions X to N (0,1)) of μ ═ κ/2 and σ ═ 1. lkRepresenting the picking distance between the bin (each level on each shelf) and the warehouse entry, and then calculating the number of levels to obtain the level value and lkThe lowest product of each type of the surface lining material is used as the surplus material target storage position (namely the scattered object target storage position) corresponding to the surplus material of the surface lining material.
According to a specific implementation manner of the embodiment of the invention, a reserve space required to be reserved for the surplus material target reserve position can be calculated, in the embodiment of the invention, the maximum surface material capable of being stored in the layer number of each shelf (each layer represents a reserve position) is measured by taking a roll as a unit, the surplus material warehousing volume number η of each type of surface material entering/leaving the warehouse at each time is calculated, and the storage space required to be reserved for the surplus material target reserve position by the volume number η is only used for warehousing and storing the surplus material of the surface material.
Further in accordance with an embodiment of the present invention, the storage set includes a bulk item target bin and a bulk item target bin. The residual storage positions of the storage positions with the scattered object target storage positions removed in the concentrated mode are the integral object target storage positions.
And step S206, determining a corresponding storage position set according to the category of the articles to be warehoused.
Specifically, according to the embodiment of the present invention, the types of the articles to be warehoused include article types and article forms, wherein the article forms include whole and scattered articles.
The item type is determined by the attribute of the item; the article form in the present invention refers to the article as a whole or as a discrete article (a part of the article is consumed), and does not refer to a certain shape state of the article.
And step S207, judging whether the article to be warehoused is a whole article or a scattered article.
According to the embodiment of the invention, after the articles are put in storage, a surface lining material checking and excess material storage link is required, wherein the checking and accepting link is used for storing the whole roll of surface lining material (complete surface lining material), the excess material storage link is used for storing the processed excess surface lining material (excess material), and the excess material needs to be placed in a storage position which is easy to take out of the storage, so that the storage position is required to be close to a storage inlet (also a storage outlet) and is also required to be easy to pick (namely the storage position which is required to be placed in the middle of a goods shelf).
Step S208, storing the articles to be warehoused to the corresponding target storage positions of the whole articles under the condition that the articles to be warehoused are the whole articles; and under the condition that the articles to be warehoused are scattered articles, storing the articles to be warehoused to the corresponding scattered article target storage positions.
Specifically, according to a specific implementation manner of the embodiment of the present invention, according to the arrangement of the storage areas, the shelves, and the storage locations, an empty storage location closest to the target storage location corresponding to the type of the article to be warehoused is calculated for warehousing the article.
If 10 storage areas are provided, respectively is xi1,ξ2,…,ξ10Each storage area has 5 shelves, each shelf has 3 layers, has 150 storage positions, and the sorting distance of each storage area and shelf from the storage export is arranged according to the sequence number, ξα,β,χShowing the alpha storage, beta shelf, chi layer. At present, 10 types of fabrics omega1,ω2,…,ω10Each type of fabric needs 15 storage positions.
Firstly, the class A lining material is omega obtained through the steps2And ω10The B-type lining material is omega3,ω7And ω8The other is C-class flour and lining material, and the storage area xi1,ξ2Is assigned to ω2And ω10Xi, reserve xi3,ξ4,ξ5Is assigned to ω3,ω7And ω8And the other areas are used for feeding the class C facing material. (embodiments of the invention require preferential allocation of bins near warehouse exits, and for ease of explanation it is assumed herein that it has been specified that each bin and its corresponding shelf are ranked in order of number from the warehouse exit, the lower the bin needs to be, the closer it is to the warehouse exit).
Taking class B surface lining material as an example, assuming that the setting of various coefficients is normal, each storage area and goods are already specifiedThe distance between the shelf and the storage outlet is arranged according to the serial number, and the result can be xi3Is assigned to ω3、ξ4Is assigned to ω7、ξ5Is assigned to ω8。
And in the step of warehousing and storing the flour and the lining materials, if the flour and the lining materials are accepted and warehoused in the target storage positions of the storage position set, warehousing and storing in a random warehousing mode. And under the condition that the target storage position is insufficient, calculating the nearest vacant storage position of the target storage position corresponding to the face material surplus material storage according to the arrangement of the storage areas, the storage shelves and the layer number, and storing the surplus material in a storage. When the residual materials are put in storage, the corresponding target storage positions are directly selected for storage, and when the storage space of the target storage positions is insufficient, the empty storage positions closest to the corresponding target storage positions are selected for storage of the articles.
According to the technical scheme of the embodiment of the invention, the storage area classification is carried out according to the information of the historical warehousing articles and the warehousing information by acquiring the information of the historical warehousing articles and the warehousing information; constructing a storage space planning model according to the storage space classification result, the picking cost and the restriction condition of each storage space in the storage space, and determining a storage space set corresponding to each type of warehousing goods according to the storage space planning model; according to the type of the articles to be put in storage, the technical means of intensively determining the target storage positions in the corresponding storage positions for article putting in storage is adopted, so that the technical problems of high article storage difficulty and high storage cost caused by lack of effective and reasonable article storage planning in the existing article storage method are solved, an effective and reasonable article putting in storage method is further provided, and the technical effects of reducing the article storage difficulty and the article storage cost are achieved.
Fig. 3 is a schematic diagram of main modules of an article warehousing device provided according to an embodiment of the invention; as shown in fig. 3, the article warehousing device 300 provided by the embodiment of the present invention mainly includes:
and the storage area classification module 301 is configured to acquire historical warehousing article information and warehousing information, and classify storage areas according to the historical warehousing article information and the warehousing information.
Through the arrangement, the storage area classification is carried out according to the historical warehousing article information and the warehousing information, so that the storage position sets corresponding to various types of warehousing articles can be determined according to the storage area classification results, the storage units corresponding to the warehousing articles can be distributed more reasonably, and the difficulty and the storage cost of warehousing and storing the articles can be reduced.
Specifically, according to an embodiment of the present invention, the historical warehousing item information includes: the types of the historical warehousing articles, and the storage spaces and the turnover rates corresponding to the various types of the historical warehousing articles; the warehousing information comprises: the storage areas, storage locations and the picking distance between the storage locations and the storage entrances in the storage.
Historical warehousing information can be acquired according to stored data in a past warehousing period (a specific time period can be adjusted according to actual conditions); the storage information is directly determined according to the storage areas, the storage shelves and the storage position distribution on the storage shelves in the storage.
According to an embodiment of the present invention, the above-mentioned storage area classification module 301 is further configured to: and determining volume order indexes of various types of historical warehousing articles according to the historical warehousing article information, and classifying storage areas according to the volume order indexes and the warehousing information.
Volume Order Index (COI, Cube-Per-Order Index): refers to the total storage space C required for storing some type of article p in a certain period of timepAnd the turnover rate f of the article in the period of timepIn particular COIp＝Cp/fp(ii) a The classified storage based on COI not only considers the turnover rate of the stored articles, but also considers the storage space of the stored articles, and further improves the efficiency and rationality of the warehousing and storage of the articles.
According to a specific implementation manner of the embodiment of the present invention, EIQ (created by suzuki earthquake, which is a japanese logistics expert, is determined for each type of article) corresponding to each type of article according to the historical warehousing article information, and three key elements, namely, an order Entry (corresponding to each warehousing Entry, for recording the type, Quantity, and the like of the warehoused articles), an article type Item, and an article Quantity (corresponding to the Quantity of the warehoused articles) are mainly considered, and then storage area classification is performed according to the COI index and EIQ analysis method.
Further, according to the embodiment of the present invention, the article warehousing device 300 further includes an average storage amount determining module, configured to determine an average storage amount of each type of historical warehousing article according to the historical warehousing article information; the above-mentioned reservoir classification module 301 is further configured to: sorting the volume order indexes of various types of historical warehousing articles according to the numerical value, storing and classifying the historical warehousing articles according to the sorting result, and classifying the storage areas according to the storage classification result, the average storage amount, the warehousing information and the storage area classification rule.
According to a specific implementation manner of the embodiment of the present invention, the COI values corresponding to all types of historical warehousing articles are arranged in the order from small to large, and then the historical warehousing articles are sorted according to the ratio of 2:3:5 (the category refers to a large category, which includes a plurality of specific warehousing article categories), that is, the top 20% of the historical warehousing articles are classified as a category, the middle 50% of the articles are classified as a category B, and the last 50% of the historical warehousing articles are classified as a category C. The specific storage classification ratio may be set according to actual conditions, the numerical values corresponding to the above ratios are only examples, and similarly, the grades of the specific classification categories may also be set according to actual conditions, and are not limited to the A, B, C categories described in the above embodiments of the present invention.
According to another specific implementation manner of the embodiment of the present invention, the average storage amount of each type of warehousing articles is obtained by calculating the total warehousing storage data of each type of warehousing articles in multiple inventories in the extractable historical article warehousing information, then storage classification results of the historical warehousing data are combined to obtain A, B, C types of corresponding storage data (i.e. storage units required by each type in A, B, C), storage area classification is performed by combining the warehousing information and the storage area classification rules, and the storage area required by each type (i.e. the aforementioned A, B, C types) of historical warehousing articles is determined.
According to a specific implementation manner of the embodiment of the present invention, the storage area classification rule is an ABC classification rule, which is also called an ABC classification management inventory control method and a primary and secondary factor analysis method and is originally created by the italian economist vilfreudeno pareto. The ABC analysis method is an analysis method commonly used in storage management, and is an analysis method for performing classification queuing, distinguishing emphasis from generality and determining management modes differently according to the main characteristics of things in technical or economic aspects. It is also called ABC analysis because it divides the objects being analyzed into A, B, C three classes. The specific proportion settings for the A, B, C categories can be adjusted according to actual conditions.
The storage location set determining module 302 is configured to construct a storage location planning model according to the storage area classification result, the picking cost of each storage location in the storage area, and the restriction condition, and determine a storage location set corresponding to each type of warehoused goods according to the storage location planning model.
Through the arrangement, the storage units corresponding to the warehoused articles are refined to the storage level, so that the storage units corresponding to various types of warehoused articles are more accurate, and the warehousing difficulty of the articles is obviously reduced.
Specifically, according to the embodiment of the present invention, the storage area classification result indicates the picking distance between each storage position in the storage area and the storage entrance and the picking frequency of each type of historical warehousing item.
Wherein, the picking frequency is determined according to the picking amount in a certain time; the picking distance comprises a horizontal distance and a vertical distance, the horizontal picking distance from the storage entrance to the same shelf is equal, and the vertical picking distances from the storage positions of different levels to the storage entrance to the same shelf are respectively unequal.
Further, according to an embodiment of the present invention, the storage bit set determining module 302 is further configured to: and constructing a storage space planning model according to the picking distance and picking cost corresponding to each storage space, the picking frequency corresponding to each type of historical warehousing article and the constraint conditions.
It should be noted that, in the process of constructing the storage space planning model, the picking frequency corresponding to each type of historical warehousing item needs to be converted into the picking amount in the corresponding picking period to participate in the construction of the storage space planning model.
Further, according to a specific implementation manner of the embodiment of the present invention, for an article warehousing apparatus including scattered articles, the storage location set determining module 302 is further configured to: and constructing a storage space planning model according to the picking distance and picking cost corresponding to each storage space, the picking frequency corresponding to each type of historical warehousing article, the warehousing coefficient of scattered articles of each storage space and the constraint conditions. The warehousing frequency of the scattered articles in the storage positions in the picking period is indicated by the warehousing coefficient of the scattered articles of each storage position, and the higher the warehousing frequency of the scattered articles is, the larger the corresponding warehousing coefficient of the scattered articles is.
According to the embodiment of the invention, the constraint conditions comprise warehouse entry article type constraint and storage position constraint.
And (4) restricting the types of the articles to be put in storage: each storage unit (storage position) can only store one type of article;
and (4) storage position constraint: the reserve is an 0/1 variable that can only be allocated to a certain type of item or not.
And the article warehousing module 303 is configured to determine a target storage location in the corresponding storage location set according to the type of the article to be warehoused for article warehousing.
Specifically, according to the embodiment of the present invention, the types of the articles to be warehoused include article types and article forms, wherein the article forms include whole and scattered articles.
The item type is determined by the attribute of the item; the article form in the present invention refers to only the article as a whole article or as a discrete article (a part of a consumption point), and does not refer to a certain shape state of the article.
According to an embodiment of the present invention, the article warehousing device 300 further includes a scattered article target storage location determining module, and before the step of determining a target storage location in a corresponding storage location set for article warehousing storage according to the type of the article to be warehoused, the scattered article target storage location determining module is configured to: determining the level numerical values corresponding to different levels of each shelf in the warehouse according to a normal distribution function, and determining the target storage positions of scattered articles corresponding to each type of warehoused articles according to the level numerical values, the picking distance between each storage position and the warehouse entrance and the storage position set corresponding to each type of warehoused articles.
For the articles to be stored which have an integral state and a scattered state, the determined storage position set is divided into the scattered article target storage position and the integral article target storage position through the setting, the articles can be stored in a warehouse more effectively, the storage positions which are concentrated and are closer to the storage inlet can be set as the scattered article target storage positions, and the scattered articles can be discharged from the warehouse preferentially.
Specifically, according to an embodiment of the present invention, the storage set includes a scattered item target bin and a whole item target bin. The residual storage positions of the storage positions with the scattered object target storage positions removed in the concentrated mode are the integral object target storage positions.
Further, according to the embodiment of the present invention, the article warehousing module 303 is further configured to: determining a corresponding storage position set according to the category of the articles to be warehoused, and storing the articles to be warehoused to the corresponding target storage positions of the whole articles under the condition that the articles to be warehoused are the whole articles; and under the condition that the articles to be warehoused are scattered articles, storing the articles to be warehoused to the corresponding scattered article target storage positions.
And when the articles to be warehoused are warehoused and stored, randomly warehousing the articles in the corresponding target storage positions.
According to an embodiment of the present invention, the article warehousing device 300 further includes an empty storage location determining module, and when the target storage location corresponding to the article to be warehoused is not an empty storage location, the empty storage location determining module is configured to: and determining corresponding empty storage positions according to the picking distance between each storage position and the storage entrance to store the articles in a warehouse.
Specifically, according to a specific implementation manner of the embodiment of the present invention, according to the arrangement of the storage areas, the shelves, and the storage locations, an empty storage location closest to the target storage location corresponding to the type of the article to be warehoused is calculated for warehousing the article.
In particular, according to an embodiment of the present invention, the above-mentioned article is an article for production in the discrete manufacturing industry. Such as lining materials in the clothing industry, raw materials in the chemical industry and the like.
According to the technical scheme of the embodiment of the invention, the storage area classification is carried out according to the information of the historical warehousing articles and the warehousing information by acquiring the information of the historical warehousing articles and the warehousing information; constructing a storage space planning model according to the storage space classification result, the picking cost and the restriction condition of each storage space in the storage space, and determining a storage space set corresponding to each type of warehousing goods according to the storage space planning model; according to the type of the articles to be put in storage, the technical means of intensively determining the target storage positions in the corresponding storage positions for article putting in storage is adopted, so that the technical problems of high article storage difficulty and high storage cost caused by lack of effective and reasonable article storage planning in the existing article storage method are solved, an effective and reasonable article putting in storage method is further provided, and the technical effects of reducing the article storage difficulty and the article storage cost are achieved.
Fig. 4 illustrates an exemplary system architecture 400 of an item-warehousing method or an item-warehousing device to which embodiments of the invention may be applied.
As shown in fig. 4, the system architecture 400 may include terminal devices 401, 402, 403, a network 404, and a server 405 (this architecture is merely an example, and the components included in a particular architecture may be adapted according to application specific circumstances). The network 404 serves as a medium for providing communication links between the terminal devices 401, 402, 403 and the server 405. Network 404 may include various types of connections, such as wire, wireless communication links, or fiber optic cables, to name a few.
A user may use terminal devices 401, 402, 403 to interact with a server 405 over a network 404 to receive or send messages or the like. The terminal devices 401, 402, 403 may have installed thereon various communication client applications, such as shopping-like applications, web browser applications, search-like applications, instant messaging tools, mailbox clients, social platform software, etc. (by way of example only).
The terminal devices 401, 402, 403 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop portable computers, desktop computers, and the like.
The server 405 may be a server providing various services, such as a background management server (for example only) providing support for shopping websites browsed by users using the terminal devices 401, 402, 403. The background management server may analyze and perform other processing on the received data such as the historical warehousing article information and the warehousing information, and feed back a processing result (for example, a storage location set corresponding to each type of warehousing article — only an example) to the terminal device.
It should be noted that the article warehousing method provided by the embodiment of the present invention is generally executed by the server 405, and accordingly, the article warehousing device is generally disposed in the server 405.
It should be understood that the number of terminal devices, networks, and servers in fig. 4 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
Referring now to FIG. 5, shown is a block diagram of a computer system 500 suitable for use with a terminal device implementing an embodiment of the present invention. The terminal device shown in fig. 5 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present invention.
As shown in fig. 5, the computer system 500 includes a Central Processing Unit (CPU)501 that can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM)502 or a program loaded from a storage section 508 into a Random Access Memory (RAM) 503. In the RAM 503, various programs and data necessary for the operation of the system 500 are also stored. The CPU 501, ROM 502, and RAM 503 are connected to each other via a bus 504. An input/output (I/O) interface 505 is also connected to bus 504.
The following components are connected to the I/O interface 505: an input portion 506 including a keyboard, a mouse, and the like; an output portion 507 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage portion 508 including a hard disk and the like; and a communication section 509 including a network interface card such as a LAN card, a modem, or the like. The communication section 509 performs communication processing via a network such as the internet. The driver 510 is also connected to the I/O interface 505 as necessary. A removable medium 511 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 510 as necessary, so that a computer program read out therefrom is mounted into the storage section 508 as necessary.
In particular, according to the embodiments of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication section 509, and/or installed from the removable medium 511. The computer program performs the above-described functions defined in the system of the present invention when executed by the Central Processing Unit (CPU) 501.
It should be noted that the computer readable medium shown in the present invention can be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present invention, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present invention, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The modules described in the embodiments of the present invention may be implemented by software or hardware. The described modules may also be provided in a processor, which may be described as: a processor comprises a storage area classification module, a storage position set determination module and an article warehousing module. The names of the modules do not limit the modules themselves under certain conditions, for example, the storage area classification module may also be described as a "module for acquiring information of historical warehoused articles and warehousing information and performing storage area classification according to the information of the historical warehoused articles and the warehousing information".
As another aspect, the present invention also provides a computer-readable medium that may be contained in the apparatus described in the above embodiments; or may be separate and not incorporated into the device. The computer readable medium carries one or more programs which, when executed by a device, cause the device to comprise: acquiring historical warehousing article information and warehousing information, and classifying storage areas according to the historical warehousing article information and the warehousing information; constructing a storage space planning model according to the storage space classification result, the picking cost and the restriction condition of each storage space in the storage space, and determining a storage space set corresponding to each type of warehousing goods according to the storage space planning model; and according to the types of the articles to be warehoused, determining a target storage position in the corresponding storage position set for warehousing and storing the articles.
According to the technical scheme of the embodiment of the invention, the storage area classification is carried out according to the information of the historical warehousing articles and the warehousing information by acquiring the information of the historical warehousing articles and the warehousing information; constructing a storage space planning model according to the storage space classification result, the picking cost and the restriction condition of each storage space in the storage space, and determining a storage space set corresponding to each type of warehousing goods according to the storage space planning model; according to the type of the articles to be put in storage, the technical means of intensively determining the target storage positions in the corresponding storage positions for article putting in storage is adopted, so that the technical problems of high article storage difficulty and high storage cost caused by lack of effective and reasonable article storage planning in the existing article storage method are solved, an effective and reasonable article putting in storage method is further provided, and the technical effects of reducing the article storage difficulty and the article storage cost are achieved.
The above-described embodiments should not be construed as limiting the scope of the invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions can occur, depending on design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (13)

1. An article warehousing method, characterized by comprising:
acquiring historical warehousing article information and warehousing information, and classifying storage areas according to the historical warehousing article information and the warehousing information;
constructing a storage space planning model according to the storage space classification result, the picking cost and the restriction condition of each storage space in the storage space, and determining a storage space set corresponding to each type of warehousing goods according to the storage space planning model;
and according to the types of the articles to be warehoused, determining a target storage position in the corresponding storage position set for warehousing and storing the articles.
2. The article warehousing method according to claim 1, wherein the historical warehousing article information includes: the types of the historical warehousing articles, and the storage spaces and the turnover rates corresponding to the various types of the historical warehousing articles; the warehousing information includes: the storage areas, storage locations and the picking distance between the storage locations and the storage entrances in the storage.
3. The method according to claim 1, wherein the step of classifying storage areas according to the historical warehousing item information and the warehousing information comprises: and determining volume order indexes of various types of historical warehousing articles according to the historical warehousing article information, and classifying storage areas according to the volume order indexes and the warehousing information.
4. The article warehousing method according to claim 3, wherein the step of determining the average storage amount of each type of historical warehoused article according to the historical warehousing article information, and the step of classifying the storage areas according to the volume order index and the warehousing information comprises: and sequencing the volume order indexes of various types of historical warehousing articles according to the numerical values, storing and classifying the historical warehousing articles according to sequencing results, and classifying storage areas according to storage and classification results, the average storage amount, the warehousing information and storage area classification rules.
5. The method according to claim 1, wherein the storage area classification result indicates a picking distance between each storage position in the storage area and a storage entrance and a picking frequency of each type of historical warehousing item, and the step of constructing the storage position planning model according to the storage area classification result, the picking cost of each storage position in the storage area and constraint conditions comprises: and constructing a storage space planning model according to the picking distance and picking cost corresponding to each storage space, the picking frequency corresponding to each type of historical warehousing article and the constraint conditions.
6. The method according to claim 1, wherein the constraint conditions include a warehousing item type constraint and a storage location constraint.
7. The method according to claim 1, wherein the types of the articles to be warehoused include article categories and article forms, wherein the article forms include whole and scattered articles; before the step of determining a target storage location in a corresponding storage location set for article warehousing storage according to the type of the article to be warehoused, the article warehousing method further comprises the following steps: determining the level numerical values corresponding to different levels of each shelf in the warehouse according to a normal distribution function, and determining the target storage positions of the scattered articles corresponding to the warehousing articles of each type according to the level numerical values, the picking distance between each storage position and the warehousing entrance and the storage position set corresponding to the warehousing articles of each type.
8. The method according to claim 7, wherein the storage set includes target storage locations of scattered articles and target storage locations of whole articles, and the step of determining the target storage locations in the corresponding storage location set for storage of the articles according to the types of the articles to be stored comprises: determining a corresponding storage position set according to the category of the articles to be warehoused, and storing the articles to be warehoused to the corresponding target storage positions of the whole articles under the condition that the articles to be warehoused are the whole articles; and under the condition that the articles to be warehoused are scattered articles, storing the articles to be warehoused to the corresponding scattered article target storage positions.
9. The article warehousing method according to claim 1, wherein in a case where the target storage location corresponding to the article to be warehoused is not an empty storage location, the article warehousing method further comprises: and determining corresponding empty storage positions according to the picking distance between each storage position and the storage entrance to store the articles in a warehouse.
10. The item warehousing method according to any one of claims 1 to 9, characterized in that the items are items for production in a discrete manufacturing industry.
11. An article warehousing device, characterized by comprising:
the storage area classification module is used for acquiring historical warehousing article information and warehousing information and classifying the storage areas according to the historical warehousing article information and the warehousing information;
the storage place set determining module is used for constructing a storage place planning model according to the storage area classification result, the picking cost and the restriction condition of each storage place in the storage area, and determining a storage place set corresponding to each type of warehousing goods according to the storage place planning model;
and the article warehousing module is used for determining a target storage position in the corresponding storage position set according to the type of the article to be warehoused for article warehousing storage.
12. An electronic device, comprising:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-10.
13. A computer-readable medium, on which a computer program is stored, which, when being executed by a processor, carries out the method according to any one of claims 1-10.
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